What runtime does LLMling require?
Python 3.12 or higher is required; the package is 100% typed and pydantic(-ai) based.
@phil65
基本信息
Easy MCP (Model Context Protocol) servers and AI agents, defined as YAML.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"LLMling": {
"command": "uvx",
"args": [
"mcp-server-llmling@latest",
"start",
"path/to/your/config.yml"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
LLMling is a Python framework for declarative LLM application development focused on resource management, prompt templates, and tool execution. It provides a YAML-based configuration system and serves as the backend for an MCP server and a pydantic-AI based Agent.
Use the CLI to manage configurations and interact with components (llmling config init, llmling resource list, llmling tool call, llmling prompt show). Integrate with agents via Python code using RuntimeConfig and LLMlingAgent. Start an MCP server for editors like Zed or Claude Desktop using uvx mcp-server-llmling@latest start.
Python 3.12 or higher is required; the package is 100% typed and pydantic(-ai) based.
LLMling uses a YAML-based configuration system where you define resources, prompts, and tools declaratively.
LLMling can be used as an MCP server with Zed Editor (via `settings.json`) or Claude Desktop (via `claude_desktop_config.json`).
Yes, resources like `path` and `image` types support file watching with configurable patterns and exclusion rules.
Resource groups allow you to group related resources for easier access, such as grouping together resources used for code review.
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